Issue 2, 2023

Predictive chemistry: machine learning for reaction deployment, reaction development, and reaction discovery

Abstract

The field of predictive chemistry relates to the development of models able to describe how molecules interact and react. It encompasses the long-standing task of computer-aided retrosynthesis, but is far more reaching and ambitious in its goals. In this review, we summarize several areas where predictive chemistry models hold the potential to accelerate the deployment, development, and discovery of organic reactions and advance synthetic chemistry.

Graphical abstract: Predictive chemistry: machine learning for reaction deployment, reaction development, and reaction discovery

Article information

Article type
Review Article
Submitted
12 9月 2022
Accepted
25 11月 2022
First published
28 11月 2022
This article is Open Access

All publication charges for this article have been paid for by the Royal Society of Chemistry
Creative Commons BY license

Chem. Sci., 2023,14, 226-244

Predictive chemistry: machine learning for reaction deployment, reaction development, and reaction discovery

Z. Tu, T. Stuyver and C. W. Coley, Chem. Sci., 2023, 14, 226 DOI: 10.1039/D2SC05089G

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. You can use material from this article in other publications without requesting further permissions from the RSC, provided that the correct acknowledgement is given.

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